The last 10 years have seen the emergence of wearable personal health tracking devices as a mainstream
industry; however, they remain limited by battery lifetime, specific sensor selection, and a market motivated by a
focus on short- term fitness metrics (e.g., steps/day). This hampers the development of a potentially much broader
application area based on optimization around biomedical theory for long- term diagnostic discovery. As new
biometric sensors come online, the ideal platform enabling the gathering of long-term diagnostic data would have
the built-in extensibility to allow testing of different sensor combinations in different research settings to discover
what kinds of data can be most useful for specific biomedical applications. Here we present the first generation of
a reconfigurable wrist-mounted sensor device measuring 7x4x2cm and weighing 51g with battery (29g without). In
its current configuration, it has recorded skin temperature, acceleration, and light exposure; these three variables
allow prediction of internal circadian rhythms, as an example of the application of biological theory to enhance
pattern detection. This generation is capable of operating long-term with minimal day-to-day disruption via easily
exchangeable batteries, and has enough space for several months of data sampling to gather long-term diagnostic
metrics. Future developments will include the addition of energy scavenging and a wireless mesh network for
ambient data collection, the combination of which will allow uninterrupted data to be gathered without depending
on the user.